The APEX Quantitative Proteomics Tool: generating protein quantitation estimates from LC-MS/MS proteomics results

Bioinformatics Tools and Knowledgebases to Assist Generating Targeted Assays for Plasma Proteomics

In targeted proteomics experiments, selecting the appropriate proteotypic peptides as surrogate for the target protein is a crucial pre-acquisition step. This step is largely a bioinformatics exercise that involves integrating information on the peptides and proteins and using various software tools and knowledgebases. We present here a few resources that automate and simplify the selection process to a great degree. These tools and knowledgebases were developed primarily to streamline targeted proteomics assay development and include PeptidePicker, PeptidePickerDB, MRMAssayDB, MouseQuaPro, and PeptideTracker. We have used these tools to develop and document thousands of targeted proteomics assays, many of them for plasma proteins with focus on human and mouse. An important aspect in all these resources is the integrative approach on which they are based. Using these tools in the first steps of designing a singleplexed or multiplexed targeted proteomic experiment can reduce the necessary experimental steps tremendously. All the tools and knowledgebases we describe here are Web-based and freely accessible so scientists can query the information conveniently from the browser. This chapter provides an overview of these software tools and knowledgebases, their content, and how to use them for targeted plasma proteomics. We further demonstrate how to use them with the results of the HUPO Human Plasma Proteome Project to produce a new database of 3.8 k targeted assays for known human plasma proteins. Upon experimental validation, these assays should help in the further quantitative characterizing of the plasma proteome.

Extracellular Vesicle Proteomes Shed Light on the Evolutionary, Interactive, and Functional Divergence of Their Biogenesis Mechanisms

Extracellular vesicles (EVs) are membranous structures containing bioactive molecules, secreted by most cells into the extracellular environment. EVs are classified by their biogenesis mechanisms into two major subtypes: ectosomes (enriched in large EVs; lEVs), budding directly from the plasma membrane, which is common in both prokaryotes and eukaryotes, and exosomes (enriched in small EVs; sEVs) generated through the multivesicular bodies via the endomembrane system, which is unique to eukaryotes. Even though recent proteomic analyses have identified key proteins associated with EV subtypes, there has been no systematic analysis, thus far, to support the general validity and utility of current EV subtype separation methods, still largely dependent on physical properties, such as vesicular size and sedimentation. Here, we classified human EV proteomic datasets into two main categories based on distinct centrifugation protocols commonly used for isolating sEV or lEV fractions. We found characteristic, evolutionarily conserved profiles of sEV and lEV proteins linked to their respective biogenetic origins. This may suggest that the evolutionary trajectory of vesicular proteins may result in a membership bias toward specific EV subtypes. Protein-protein interaction (PPI) network analysis showed that vesicular proteins formed distinct clusters with proteins in the same EV fraction, providing evidence for the existence of EV subtype-specific protein recruiters. Moreover, we identified functional modules enriched in each fraction, including multivesicular body sorting for sEV, and mitochondria cellular respiration for lEV proteins. Our analysis successfully captured novel features of EVs embedded in heterogeneous proteomics studies and suggests specific protein markers and signatures to be used as quality controllers in the isolation procedure for subtype-enriched EV fractions.

Development of an Ocean Protein Portal for Interactive Discovery and Education

Proteins are critical in catalyzing chemical reactions, forming key cellular structures, and in regulating cellular processes. Investigation of marine microbial proteins by metaproteomics methods enables the discovery of numerous aspects of microbial biogeochemical processes. However, these datasets present big data challenges as they often involve many samples collected across broad geospatial and temporal scales, resulting in thousands of protein identifications, abundances, and corresponding annotation information. The Ocean Protein Portal (OPP) was created to enable data sharing and discovery among multiple scientific domains and serve both research and education functions. The portal focuses on three use case questions: "Where is my protein of interest?", "Who makes it?", and "How much is there?" and provides profile and section visualizations, real-time taxonomic analysis, and links to metadata, sequence analysis, and other external resources to enable connections to be made between biogeochemical and proteomics datasets.

Bringing New Methods to the Seed Proteomics Platform: Challenges and Perspectives

For centuries, crop plants have represented the basis of the daily human diet. Among them, cereals and legumes, accumulating oils, proteins, and carbohydrates in their seeds, distinctly dominate modern agriculture, thus play an essential role in food industry and fuel production. Therefore, seeds of crop plants are intensively studied by food chemists, biologists, biochemists, and nutritional physiologists. Accordingly, seed development and germination as well as age- and stress-related alterations in seed vigor, longevity, nutritional value, and safety can be addressed by a broad panel of analytical, biochemical, and physiological methods. Currently, functional genomics is one of the most powerful tools, giving direct access to characteristic metabolic changes accompanying plant development, senescence, and response to biotic or abiotic stress. Among individual post-genomic methodological platforms, proteomics represents one of the most effective ones, giving access to cellular metabolism at the level of proteins. During the recent decades, multiple methodological advances were introduced in different branches of life science, although only some of them were established in seed proteomics so far. Therefore, here we discuss main methodological approaches already employed in seed proteomics, as well as those still waiting for implementation in this field of plant research, with a special emphasis on sample preparation, data acquisition, processing, and post-processing. Thereby, the overall goal of this review is to bring new methodologies emerging in different areas of proteomics research (clinical, food, ecological, microbial, and plant proteomics) to the broad society of seed biologists.

Molecular Diversification of the Seminal Fluid Proteome in a Recently Diverged Passerine Species Pair

Seminal fluid proteins (SFPs) mediate an array of postmating reproductive processes that influence fertilization and fertility. As such, it is widely held that SFPs may contribute to postmating, prezygotic reproductive barriers between closely related taxa. We investigated seminal fluid (SF) diversification in a recently diverged passerine species pair (Passer domesticus and Passer hispaniolensis) using a combination of proteomic and comparative evolutionary genomic approaches. First, we characterized and compared the SF proteome of the two species, revealing consistencies with known aspects of SFP biology and function in other taxa, including the presence and diversification of proteins involved in immunity and sperm maturation. Second, using whole-genome resequencing data, we assessed patterns of genomic differentiation between house and Spanish sparrows. These analyses detected divergent selection on immunity-related SF genes and positive selective sweeps in regions containing a number of SF genes that also exhibited protein abundance diversification between species. Finally, we analyzed the molecular evolution of SFPs across 11 passerine species and found a significantly higher rate of positive selection in SFPs compared with the rest of the genome, as well as significant enrichments for functional pathways related to immunity in the set of positively selected SF genes. Our results suggest that selection on immunity pathways is an important determinant of passerine SF composition and evolution. Assessing the role of immunity genes in speciation in other recently diverged taxa should be prioritized given the potential role for immunity-related proteins in reproductive incompatibilities in Passer sparrows.

Multi-omics tools for studying microbial biofilms: current perspectives and future directions

The advent of omics technologies has greatly improved our understanding of microbial biology, particularly in the last two decades. The field of microbial biofilms is, however, relatively new, consolidated in the 1980s. The morphogenic switching by microbes from planktonic to biofilm phenotype confers numerous survival advantages such as resistance to desiccation, antibiotics, biocides, ultraviolet radiation, and host immune responses, thereby complicating treatment strategies for pathogenic microorganisms. Hence, understanding the mechanisms governing the biofilm phenotype can result in efficient treatment strategies directed specifically against molecular markers mediating this process. The application of omics technologies for studying microbial biofilms is relatively less explored and holds great promise in furthering our understanding of biofilm biology. In this review, we provide an overview of the application of omics tools such as transcriptomics, proteomics, and metabolomics as well as multi-omics approaches for studying microbial biofilms in the current literature. We also highlight how the use of omics tools directed at various stages of the biological information flow, from genes to metabolites, can be integrated via multi-omics platforms to provide a holistic view of biofilm biology. Following this, we propose a future artificial intelligence-based multi-omics platform that can predict the pathways associated with different biofilm phenotypes.

Variability in protein cargo detection in technical and biological replicates of exosome-enriched extracellular vesicles

Exosomes are extracellular vesicles (EVs) of ~20-200 nm diameter that shuttle DNAs, RNAs, proteins and other biomolecules between cells. The large number of biomolecules present in exosomes demands the frequent use of high-throughput analysis. This, in turn, requires technical replicates (TRs), and biological replicates (BRs) to produce accurate results. As the number and abundance of identified biomolecules varies between replicates (Rs), establishing the replicate variability predicted for the event under study is essential in determining the number of Rs required. Although there have been few reports of replicate variability in high throughput biological data, none of them focused on exosomes. Herein, we determined the replicate variability in protein profiles found in exosomes released from 3 lung adenocarcinoma cell lines, H1993, A549 and H1975. Since exosome isolates are invariably contaminated by a small percentage of ~200-300 nm microvesicles, we refer to our samples as exosome-enriched EVs (EE-EVs). We generated BRs of EE-EVs from each cell line, and divided each group into 3 TRs. All Rs were analyzed by liquid chromatography/mass spectrometry (LC/MS/MS) and customized bioinformatics and biostatistical workflows (raw data available via ProteomeXchange: PXD012798). We found that the variability among TRs as well as BRs, was largely qualitative (protein present or absent) and higher among BRs. By contrast, the quantitative (protein abundance) variability was low, save for the H1975 cell line where the quantitative variability was significant. Importantly, our replicate strategy identified 90% of the most abundant proteins, thereby establishing the utility of our approach.

Methods and Algorithms for Quantitative Proteomics by Mass Spectrometry

Protein quantitation by mass spectrometry has always been a resourceful technique in protein discovery, and more recently it has leveraged the advent of clinical proteomics. A single mass spectrometry analysis experiment provides identification and quantitation of proteins as well as information on posttranslational modifications landscape. By contrast, protein array technologies are restricted to quantitation of targeted proteins and their modifications. Currently, there are an overwhelming number of quantitative mass spectrometry methods for protein and peptide quantitation. The aim here is to provide an overview of the most common mass spectrometry methods and algorithms used in quantitative proteomics and discuss the computational aspects to obtain reliable quantitative measures of proteins, peptides and their posttranslational modifications. The development of a pipeline using commercial or freely available software is one of the main challenges in data analysis of many experimental projects. Recent developments of R statistical programming language make it attractive to fully develop pipelines for quantitative proteomics. We discuss concepts of quantitative proteomics that together with current R packages can be used to build highly customizable pipelines.

Comparative Proteomics Analysis of Human Liver Microsomes and S9 Fractions

Human liver microsomes (HLM) and human liver S9 fractions (HLS9) are commonly used to study drug metabolism in vitro. However, a quantitative comparison of HLM and HLS9 proteomes is lacking, resulting in the arbitrary selection of one hepatic preparation over another and in difficulties with data interpretation. In this study, we applied a label-free global absolute quantitative proteomics method to the analysis of HLS9 and the corresponding HLM prepared from 102 individual human livers. A total of 3137 proteins were absolutely quantified, and 3087 of those were determined in both HLM and HLS9. Protein concentrations were highly correlated between the two hepatic preparations (R = 0.87, P < 0.0001). We reported the concentrations of 98 drug-metabolizing enzymes (DMEs) and 51 transporters, and demonstrated significant differences between their abundances in HLM and HLS9. We also revealed the protein-protein correlations among these DMEs and transporters and the sex effect on the HLM and HLS9 proteomes. Additionally, HLM and HLS9 displayed distinct expression patterns for protein markers of cytosol and various cellular organelles. Moreover, we evaluated the interindividual variability of three housekeeping proteins, and identified five proteins with low variation across individuals that have the potential to serve as new internal controls for western blot experiments. In summary, these results will lead to better understanding of data obtained from HLM and HLS9 and assist in in vitro-in vivo extrapolations. Knowing the differences between HLM and HLS9 also allows us to make better-informed decisions when choosing between these two hepatic preparations for in vitro drug metabolism studies. SIGNIFICANCE STATEMENT: This investigation revealed significant differences in protein concentrations of drug-metabolizing enzymes and transporters between human liver microsomes and S9 fractions. We also determined the protein-protein correlations among the drug-metabolizing enzymes and transporters and the sex effect on the proteomes of these two hepatic preparations. The results will help interpret data obtained from these two preparations and allow us to make more informed decisions when choosing between human liver microsomes and S9 fractions for in vitro drug metabolism studies.

Tetrahydrobiopterin enhances mitochondrial biogenesis and cardiac contractility via stimulation of PGC1α signaling

Tetrahydrobiopterin (BH4) shows therapeutic potential as an endogenous target in cardiovascular diseases. Although it is involved in cardiovascular metabolism and mitochondrial biology, its mechanisms of action are unclear. We investigated how BH4 regulates cardiovascular metabolism using an unbiased multiple proteomics approach with a sepiapterin reductase knock-out (Spr-/-) mouse as a model of BH4 deficiency. Spr-/- mice exhibited a shortened life span, cardiac contractile dysfunction, and morphological changes. Multiple proteomics and systems-based data-integrative analyses showed that BH4 deficiency altered cardiac mitochondrial oxidative phosphorylation. Along with decreased transcription of major mitochondrial biogenesis regulatory genes, including Ppargc1a, Ppara, Esrra, and Tfam, Spr-/- mice exhibited lower mitochondrial mass and severe oxidative phosphorylation defects. Exogenous BH4 supplementation, but not nitric oxide supplementation or inhibition, rescued these cardiac and mitochondrial defects. BH4 supplementation also recovered mRNA and protein levels of PGC1α and its target proteins involved in mitochondrial biogenesis (mtTFA and ERRα), antioxidation (Prx3 and SOD2), and fatty acid utilization (CD36 and CPTI-M) in Spr-/- hearts. These results indicate that BH4-activated transcription of PGC1α regulates cardiac energy metabolism independently of nitric oxide and suggests that BH4 has therapeutic potential for cardiovascular diseases involving mitochondrial dysfunction.

Female novelty and male status dynamically modulate ejaculate expenditure and seminal fluid proteome over successive matings in red junglefowl

Theory predicts that males will strategically invest in ejaculates according to the value of mating opportunities. While strategic sperm allocation has been studied extensively, little is known about concomitant changes in seminal fluid (SF) and its molecular composition, despite increasing evidence that SF proteins (SFPs) are fundamental in fertility and sperm competition. Here, we show that in male red junglefowl, Gallus gallus, along with changes in sperm numbers and SF investment, SF composition changed dynamically over successive matings with a first female, immediately followed by mating with a second, sexually novel female. The SF proteome exhibited a pattern of both protein depletion and enrichment over successive matings, including progressive increases in immunity and plasma proteins. Ejaculates allocated to the second female had distinct proteomic profiles, where depletion of many SFPs was compensated by increased investment in others. This response was partly modulated by male social status: when mating with the second, novel female, subdominants (but not dominants) preferentially invested in SFPs associated with sperm composition, which may reflect status-specific differences in mating rates, sperm maturation and sperm competition. Global proteomic SF analysis thus reveals that successive matings trigger rapid, dynamic SFP changes driven by a combination of depletion and strategic allocation.

Methods review: Mass spectrometry analysis of RNAPII complexes

RNA Polymerase II (RNAPII) is responsible for transcribing multiple RNA species throughout eukaryotes. A variety of protein-protein interactions occur throughout the transcription cycle for coordinated regulation of transcription initiation, elongation, and/or termination. Taking a proteomics approach to study RNAPII transcription thereby offers a comprehensive view of both RNAPII biology and the variety of proteins that regulate the process itself. This review will focus on how mass spectrometry (MS) methods have expanded understanding of RNAPII and its transcription-regulatory interaction partners. The application of affinity purification mass spectrometry has led to the discovery of a number of novel groups of proteins that regulate an array of RNAPII biology ranging from nuclear import to regulation of phosphorylation state. Additionally, a number of methods have been developed using mass spectrometry to measure protein subunit stoichiometry within and across protein complexes and to perform various types of architectural analysis using structural proteomics approaches. The key methods that we will focus on related to RNAPII mass spectrometry analyses include: affinity purification mass spectrometry, protein post-translational modification analysis, crosslinking mass spectrometry, and native mass spectrometry.

Proteins, Transcripts, and Genetic Architecture of Seminal Fluid and Sperm in the Mosquito Aedes aegypti

The yellow fever mosquito, Aedes aegypti,, transmits several viruses causative of serious diseases, including dengue, Zika, and chikungunya. Some proposed efforts to control this vector involve manipulating reproduction to suppress wild populations or to replace them with disease-resistant mosquitoes. The design of such strategies requires an intimate knowledge of reproductive processes, yet our basic understanding of reproductive genetics in this vector remains largely incomplete. To accelerate future investigations, we have comprehensively catalogued sperm and seminal fluid proteins (SFPs) transferred to females in the ejaculate using tandem mass spectrometry. By excluding female-derived proteins using an isotopic labeling approach, we identified 870 sperm proteins and 280 SFPs. Functional composition analysis revealed parallels with known aspects of sperm biology and SFP function in other insects. To corroborate our proteome characterization, we also generated transcriptomes for testes and the male accessory glands-the primary contributors to Ae. aegypti, sperm and seminal fluid, respectively. Differential gene expression of accessory glands from virgin and mated males suggests that transcripts encoding proteins involved in protein translation are upregulated post-mating. Several SFP transcripts were also modulated after mating, but >90% remained unchanged. Finally, a significant enrichment of SFPs was observed on chromosome 1, which harbors the male sex determining locus in this species. Our study provides a comprehensive proteomic and transcriptomic characterization of ejaculate production and composition and thus provides a foundation for future investigations of Ae. aegypti, reproductive biology, from functional analysis of individual proteins to broader examination of reproductive processes.

Label-free absolute protein quantification with data-independent acquisition

Despite data-independent acquisition (DIA) has been increasingly used for relative protein quantification, DIA-based label-free absolute quantification method has not been fully established. Here we present a novel DIA method using the TPA algorithm (DIA-TPA) for the absolute quantification of protein expressions in human liver microsomal and S9 samples. To validate this method, both data-dependent acquisition (DDA) and DIA experiments were conducted on 36 individual human liver microsome and S9 samples. The MS2-based DIA-TPA was able to quantify approximately twice as many proteins as the MS1-based DDA-TPA method, whereas protein concentrations determined by the two approaches were comparable. To evaluate the accuracy of the DIA-TPA method, we absolutely quantified carboxylesterase 1 concentrations in human liver S9 fractions using an established SILAC internal standard-based proteomic assay; the SILAC results were consistent with those obtained from DIA-TPA analysis. Finally, we employed a unique algorithm in DIA-TPA to distribute the MS signals from shared peptides to individual proteins or isoforms and successfully applied the method to the absolute quantification of several drug-metabolizing enzymes in human liver microsomes. In sum, the DIA-TPA method not only can absolutely quantify entire proteomes and specific proteins, but also has the capability quantifying proteins with shared peptides. SIGNIFICANCE: Data independent acquisition (DIA) has emerged as a powerful approach for relative protein quantification at the whole proteome level. However, DIA-based label-free absolute protein quantification (APQ) method has not been fully established. In the present study, we present a novel DIA-based label-free APQ approach, named DIA-TPA, with the capability absolutely quantifying proteins with shared peptides. The method was validated by comparing the quantification results of DIA-TPA with that obtained from stable isotope-labeled internal standard-based proteomic assays.

Mass Spectrometry-Based Biomarkers in Drug Development

Advances in mass spectrometry, proteomics, protein bioanalytical approaches, and biochemistry have led to a rapid evolution and expansion in the area of mass spectrometry-based biomarker discovery and development. The last decade has also seen significant progress in establishing accepted definitions, guidelines, and criteria for the analytical validation, acceptance and qualification of biomarkers. These advances have coincided with a decreased return on investment for pharmaceutical research and development and an increasing need for better early decision making tools. Empowering development teams with tools to measure a therapeutic interventions impact on disease state and progression, measure target engagement and to confirm predicted pharmacodynamic effects is critical to efficient data-driven decision making. Appropriate implementation of a biomarker or a combination of biomarkers can enhance understanding of a drugs mechanism, facilitate effective translation from the preclinical to clinical space, enable early proof of concept and dose selection, and increases the efficiency of drug development. Here we will provide descriptions of the different classes of biomarkers that have utility in the drug development process as well as review specific, protein-centric, mass spectrometry-based approaches for the discovery of biomarkers and development of targeted assays to measure these markers in a selective and analytically precise manner.

A Guide to Mass Spectrometry-Based Quantitative Proteomics

Proteomics has become an attractive science in the postgenomic era, given its capacity to identify up to thousands of molecules in a single, complex sample and quantify them in an absolute and/or relative manner. The use of these techniques enables understanding of cellular and molecular mechanisms of diseases and other biological conditions, as well as identification and screening of protein biomarkers. Here we provide a straightforward, up-to-date compilation and comparison of the main quantitation techniques used in comparative proteomics such as in vitro and in vivo stable isotope labeling and label-free techniques. Additionally, this chapter includes common methods for data acquisition in proteomics and some appropriate methods for data processing. This compilation can serve as a reference for scientists who are new to, or already familiar with, quantitative proteomics.

Toxin-resolved antivenomics-guided assessment of the immunorecognition landscape of antivenoms

Snakebite envenoming represents a major issue in rural areas of tropical and subtropical regions across sub-Saharan Africa, South to Southeast Asia, Latin America and Oceania. Antivenoms constitute the only scientifically validated therapy for snakebite envenomings, provided they are safe, effective, affordable, accessible and administered appropriately. However, the lack of financial incentives in a technology that has remained relatively unchanged for more than a century, has contributed to some manufacturers leaving the market and others downscaling production or increasing the prices, leading to a decline in the availability and accessibility for these life-saving antidotes to millions of rural poor most at risk from snakebites in low income countries. The shortage of antivenoms can be significantly alleviated by optimizing the use of current antivenoms (through the assessment of their specific and paraspecific efficacy against the different medically relevant homologous and heterologous snake venoms) and by generating novel polyspecific antivenoms exhibiting broad clinical spectrum and wide geographic distribution range. Research on venoms has been continuously enhanced by advances in technology. Particularly, the last decade has witnessed the development of omics strategies for unravelling the toxin composition of venoms ("venomics") and to assess the immunorecognition profile of antivenoms ("antivenomics"). Here, we review recent developments and reflect on near future innovations that promise to revolutionize the mutually enlightening relationship between evolutionary and translational venomics.

Tear proteome analysis in ocular surface diseases using label-free LC-MS/MS and multiplexed-microarray biomarker validation

We analyzed the tear film proteome of patients with dry eye (DE), meibomian gland dysfunction (MGD), and normal volunteers (CT). Tear samples were collected from 70 individuals. Of these, 37 samples were analyzed using spectral-counting-based LC-MS/MS label-free quantitation, and 33 samples were evaluated in the validation of candidate biomarkers employing customized antibody microarray assays. Comparative analysis of tear protein profiles revealed differences in the expression levels of 26 proteins, including protein S100A6, annexin A1, cystatin-S, thioredoxin, phospholipase A2, antileukoproteinase, and lactoperoxidase. Antibody microarray validation of CST4, S100A6, and MMP9 confirmed the accuracy of previously reported ELISA assays, with an area under ROC curve (AUC) of 87.5%. Clinical endpoint analysis showed a good correlation between biomarker concentrations and clinical parameters. In conclusion, different sets of proteins differentiate between the groups. Apolipoprotein D, S100A6, S100A8, and ceruloplasmin discriminate best between the DE and CT groups. The differences between antileukoproteinase, phospholipase A2, and lactoperoxidase levels allow the distinction between MGD and DE, and the changes in the levels of annexin A1, clusterin, and alpha-1-acid glycoprotein 1, between MGD and CT groups. The functional network analysis revealed the main biological processes that should be examined to identify new candidate biomarkers and therapeutic targets.

Tear proteome analysis in ocular surface diseases using label-free LC-MS/MS and multiplexed-microarray biomarker validation

We analyzed the tear film proteome of patients with dry eye (DE), meibomian gland dysfunction (MGD), and normal volunteers (CT). Tear samples were collected from 70 individuals. Of these, 37 samples were analyzed using spectral-counting-based LC-MS/MS label-free quantitation, and 33 samples were evaluated in the validation of candidate biomarkers employing customized antibody microarray assays. Comparative analysis of tear protein profiles revealed differences in the expression levels of 26 proteins, including protein S100A6, annexin A1, cystatin-S, thioredoxin, phospholipase A2, antileukoproteinase, and lactoperoxidase. Antibody microarray validation of CST4, S100A6, and MMP9 confirmed the accuracy of previously reported ELISA assays, with an area under ROC curve (AUC) of 87.5%. Clinical endpoint analysis showed a good correlation between biomarker concentrations and clinical parameters. In conclusion, different sets of proteins differentiate between the groups. Apolipoprotein D, S100A6, S100A8, and ceruloplasmin discriminate best between the DE and CT groups. The differences between antileukoproteinase, phospholipase A2, and lactoperoxidase levels allow the distinction between MGD and DE, and the changes in the levels of annexin A1, clusterin, and alpha-1-acid glycoprotein 1, between MGD and CT groups. The functional network analysis revealed the main biological processes that should be examined to identify new candidate biomarkers and therapeutic targets.

Contrasting patterns of evolutionary constraint and novelty revealed by comparative sperm proteomic analysis in Lepidoptera

Background

Rapid evolution is a hallmark of reproductive genetic systems and arises through the combined processes of sequence divergence, gene gain and loss, and changes in gene and protein expression. While studies aiming to disentangle the molecular ramifications of these processes are progressing, we still know little about the genetic basis of evolutionary transitions in reproductive systems. Here we conduct the first comparative analysis of sperm proteomes in Lepidoptera, a group that exhibits dichotomous spermatogenesis, in which males produce a functional fertilization-competent sperm (eupyrene) and an incompetent sperm morph lacking nuclear DNA (apyrene). Through the integrated application of evolutionary proteomics and genomics, we characterize the genomic patterns potentially associated with the origination and evolution of this unique spermatogenic process and assess the importance of genetic novelty in Lepidopteran sperm biology.

Results

Comparison of the newly characterized Monarch butterfly (Danaus plexippus) sperm proteome to those of the Carolina sphinx moth (Manduca sexta) and the fruit fly (Drosophila melanogaster) demonstrated conservation at the level of protein abundance and post-translational modification within Lepidoptera. In contrast, comparative genomic analyses across insects reveals significant divergence at two levels that differentiate the genetic architecture of sperm in Lepidoptera from other insects. First, a significant reduction in orthology among Monarch sperm genes relative to the remainder of the genome in non-Lepidopteran insect species was observed. Second, a substantial number of sperm proteins were found to be specific to Lepidoptera, in that they lack detectable homology to the genomes of more distantly related insects. Lastly, the functional importance of Lepidoptera specific sperm proteins is broadly supported by their increased abundance relative to proteins conserved across insects.

Conclusions

Our results identify a burst of genetic novelty amongst sperm proteins that may be associated with the origin of heteromorphic spermatogenesis in ancestral Lepidoptera and/or the subsequent evolution of this system. This pattern of genomic diversification is distinct from the remainder of the genome and thus suggests that this transition has had a marked impact on lepidopteran genome evolution. The identification of abundant sperm proteins unique to Lepidoptera, including proteins distinct between specific lineages, will accelerate future functional studies aiming to understand the developmental origin of dichotomous spermatogenesis and the functional diversification of the fertilization incompetent apyrene sperm morph.

Electronic supplementary material

The online version of this article (10.1186/s12864-017-4293-2) contains supplementary material, which is available to authorized users.

Comparative Sperm Proteomics in Mouse Species with Divergent Mating Systems

Sexual selection is the pervasive force underlying the dramatic divergence of sperm form and function. Although it has been demonstrated that testis gene expression evolves rapidly, exploration of the proteomic basis of sperm diversity is in its infancy. We have employed a whole-cell proteomics approach to characterize sperm divergence among closely related Mus species that experience different sperm competition regimes and exhibit pronounced variation in sperm energetics, motility and fertilization capacity. Interspecific comparisons revealed significant abundance differences amongst proteins involved in fertilization capacity, including those that govern sperm-zona pellucida interactions, axoneme components and metabolic proteins. Ancestral reconstruction of relative testis size suggests that the reduction of zona pellucida binding proteins and heavy-chain dyneins was associated with a relaxation in sperm competition in the M. musculus lineage. Additionally, the decreased reliance on ATP derived from glycolysis in high sperm competition species was reflected in abundance decreases in glycolytic proteins of the principle piece in M. spretus and M. spicilegus. Comparison of protein abundance and stage-specific testis expression revealed a significant correlation during spermatid development when dynamic morphological changes occur. Proteins underlying sperm diversification were also more likely to be subject to translational repression, suggesting that sperm composition is influenced by the evolution of translation control mechanisms. The identification of functionally coherent classes of proteins relating to sperm competition highlights the utility of evolutionary proteomic analyses and reveals that both intensified and relaxed sperm competition can have a pronounced impact on the molecular composition of the male gamete.

Algorithms and design strategies towards automated glycoproteomics analysis

Glycoproteomics involves the study of glycosylation events on protein sequences ranging from purified proteins to whole proteome scales. Understanding these complex post-translational modification (PTM) events requires elucidation of the glycan moieties (monosaccharide sequences and glycosidic linkages between residues), protein sequences, as well as site-specific attachment of glycan moieties onto protein sequences, in a spatial and temporal manner in a variety of biological contexts. Compared with proteomics, bioinformatics for glycoproteomics is immature and many researchers still rely on tedious manual interpretation of glycoproteomics data. As sample preparation protocols and analysis techniques have matured, the number of publications on glycoproteomics and bioinformatics has increased substantially; however, the lack of consensus on tool development and code reuse limits the dissemination of bioinformatics tools because it requires significant effort to migrate a computational tool tailored for one method design to alternative methods. This review discusses algorithms and methods in glycoproteomics, and refers to the general proteomics field for potential solutions. It also introduces general strategies for tool integration and pipeline construction in order to better serve the glycoproteomics community. © 2016 Wiley Periodicals, Inc. Mass Spec Rev 36:475-498, 2017.

Proteomics analysis of bladder cancer invasion: Targeting EIF3D for therapeutic intervention

Patients with advanced bladder cancer have poor outcomes, indicating a need for more efficient therapeutic approaches. This study characterizes proteomic changes underlying bladder cancer invasion aiming for the better understanding of disease pathophysiology and identification of drug targets. High resolution liquid chromatography coupled to tandem mass spectrometry analysis of tissue specimens from patients with non-muscle invasive (NMIBC, stage pTa) and muscle invasive bladder cancer (MIBC, stages pT2+) was conducted. Comparative analysis identified 144 differentially expressed proteins between analyzed groups. These included proteins previously associated with bladder cancer and also additional novel such as PGRMC1, FUCA1, BROX and PSMD12, which were further confirmed by immunohistochemistry. Pathway and interactome analysis predicted strong activation in muscle invasive bladder cancer of pathways associated with protein synthesis e.g. eIF2 and mTOR signaling. Knock-down of eukaryotic translation initiation factor 3 subunit D (EIF3D) (overexpressed in muscle invasive disease) in metastatic T24M bladder cancer cells inhibited cell proliferation, migration, and colony formation in vitro and decreased tumor growth in xenograft models. By contrast, knocking down GTP-binding protein Rheb (which is upstream of EIF3D) recapitulated the effects of EIF3D knockdown in vitro, but not in vivo. Collectively, this study represents a comprehensive analysis of NMIBC and MIBC providing a resource for future studies. The results highlight EIF3D as a potential therapeutic target.

Label-Free and Standard-Free Absolute Quantitative Proteomics Using the "Total Protein" and "Proteomic Ruler" Approaches

Understanding biological systems and their variation upon stimuli requires knowledge on their composition, primarily including information on organization and dynamics of proteomes. The total protein approach (TPA) is a label- and standard-free method for absolute protein quantitation of proteins using large-scale proteomic data. The method relies on the assumption that the total MS signal from all identified proteins in the dataset reflects-in a biochemical sense-the total protein and the MS signal from a single protein corresponds its abundance in the studied sample. The method offers an easy way to quantify thousands of protein per sample. A related method, the "Proteomic Ruler," enables conversion of the protein abundance data calculated by TPA to compute numbers of protein copies per cell. TPA and the Proteomic Ruler are powerful tools for studying dynamics of cell architecture.

The Seminal fluid proteome of the polyandrous Red junglefowl offers insights into the molecular basis of fertility, reproductive ageing and domestication

Seminal fluid proteins (SFPs) are emerging as fundamental contributors to sexual selection given their role in post-mating reproductive events, particularly in polyandrous species where the ejaculates of different males compete for fertilisation. SFP identification however remains taxonomically limited and little is known about avian SFPs, despite extensive work on sexual selection in birds. We characterize the SF proteome of the polyandrous Red junglefowl, Gallus gallus, the wild species that gave rise to the domestic chicken. We identify 1,141 SFPs, including proteins involved in immunity and antimicrobial defences, sperm maturation, and fertilisation, revealing a functionally complex SF proteome. This includes a predominant contribution of blood plasma proteins that is conserved with human SF. By comparing the proteome of young and old males with fast or slow sperm velocity in a balanced design, we identify proteins associated with ageing and sperm velocity, and show that old males that retain high sperm velocity have distinct proteome characteristics. SFP comparisons with domestic chickens revealed both qualitative and quantitative differences likely associated with domestication and artificial selection. Collectively, these results shed light onto the functional complexity of avian SF, and provide a platform for molecular studies of fertility, reproductive ageing, and domestication.

Two distinct extracellular RNA signatures released by a single cell type identified by microarray and next-generation sequencing

Cells secrete extracellular RNA (exRNA) to their surrounding environment and exRNA has been found in many body fluids such as blood, breast milk and cerebrospinal fluid. However, there are conflicting results regarding the nature of exRNA. Here, we have separated 2 distinct exRNA profiles released by mast cells, here termed high-density (HD) and low-density (LD) exRNA. The exRNA in both fractions was characterized by microarray and next-generation sequencing. Both exRNA fractions contained mRNA and miRNA, and the mRNAs in the LD exRNA correlated closely with the cellular mRNA, whereas the HD mRNA did not. Furthermore, the HD exRNA was enriched in lincRNA, antisense RNA, vault RNA, snoRNA, and snRNA with little or no evidence of full-length 18S and 28S rRNA. The LD exRNA was enriched in mitochondrial rRNA, mitochondrial tRNA, tRNA, piRNA, Y RNA, and full-length 18S and 28S rRNA. The proteomes of the HD and LD exRNA-containing fractions were determined with LC-MS/MS and analyzed with Gene Ontology term finder, which showed that both proteomes were associated with the term extracellular vesicles and electron microscopy suggests that at least a part of the exRNA is associated with exosome-like extracellular vesicles. Additionally, the proteins in the HD fractions tended to be associated with the nucleus and ribosomes, whereas the LD fraction proteome tended to be associated with the mitochondrion.

We show that the 2 exRNA signatures released by a single cell type can be separated by floatation on a density gradient. These results show that cells can release multiple types of exRNA with substantial differences in RNA species content. This is important for any future studies determining the nature and function of exRNA released from different cells under different conditions.

Improving the Production of L-Phenylalanine by Identifying Key Enzymes Through Multi-Enzyme Reaction System in Vitro

L-Phenylalanine (L-Phe) is an important amino acid used in both food and medicinal applications. We developed an in vitro system that allowed a direct, quantitative investigation of phenylalanine biosynthesis in E. coli. Here, the absolute concentrations of six enzymes (AroK, AroL, AroA, AroC, PheA and TyrB) involved in the shikimate (SHIK) pathway were determined by a quantitative proteomics approach and in vitro enzyme titration experiments. The reconstitution of an in vitro reaction system for these six enzymes was established and their effects on the phenylalanine production were tested. The results showed that the yield of phenylalanine increased 3.0 and 2.1 times when the concentrations of shikimate kinase (AroL) and 5-enolpyruvoyl shikimate 3-phosphate (EPSP) synthase (AroA) were increased 2.5 times. Consistent results were obtained from in vivo via the overexpression of AroA in a phenylalanine-producing strain, and the titer of phenylalanine reached 62.47 g/l after 48 h cultivation in a 5-liter jar fermentor. Our quantitative findings provide a practical method to detect the potential bottleneck in a specific metabolic pathway to determine which gene products should be targeted to improve the yield of the desired product.

miR-200c dampens cancer cell migration via regulation of protein kinase A subunits

Expression of miR-200c is a molecular switch to determine cellular fate towards a mesenchymal or epithelial phenotype. miR-200c suppresses the early steps of tumor progression by preventing epithelial-mesenchymal transition (EMT) and intravasation of tumor cells. Unraveling the underlying molecular mechanisms might pinpoint to novel therapeutic options. To better understand these mechanisms it is crucial to identify targets of miR-200c. Here, we employ a combination of quantitative proteomic and bioinformatic strategies to identify novel miR-200c targets. We identify and confirm two subunits of the central cellular kinase protein kinase A (PKA), namely PRKAR1A and PRKACB, to be directly regulated by miR-200c. Notably, siRNA-mediated downregulation of both proteins phenocopies the migratory behavior of breast cancer cells after miR-200c overexpression. Patient data from publicly accessible databases supports a miR-200c-PKA axis. Thus, our study identifies the PKA heteroprotein as an important mediator of miR-200c induced repression of migration in breast cancer cells. By bioinformatics, we define a miRNA target cluster consisting of PRKAR1A, PRKAR2B, PRKACB, and COF2, which is targeted by a group of 14 miRNAs.

Obligate Biotroph Pathogens of the Genus Albugo Are Better Adapted to Active Host Defense Compared to Niche Competitors

Recent research suggested that plants behave differently under combined versus single abiotic and biotic stress conditions in controlled environments. While this work has provided a glimpse into how plants might behave under complex natural conditions, it also highlights the need for field experiments using established model systems. In nature, diverse microbes colonize the phyllosphere of Arabidopsis thaliana, including the obligate biotroph oomycete genus Albugo, causal agent of the common disease white rust. Biotrophic, as well as hemibiotrophic plant pathogens are characterized by efficient suppression of host defense responses. Lab experiments have even shown that Albugo sp. can suppress non-host resistance, thereby enabling otherwise avirulent pathogen growth. We asked how a pathogen that is vitally dependent on a living host can compete in nature for limited niche space while paradoxically enabling colonization of its host plant for competitors? To address this question, we used a proteomics approach to identify differences and similarities between lab and field samples of Albugo sp.-infected and -uninfected A. thaliana plants. We could identify highly similar apoplastic proteomic profiles in both infected and uninfected plants. In wild plants, however, a broad range of defense-related proteins were detected in the apoplast regardless of infection status, while no or low levels of defense-related proteins were detected in lab samples. These results indicate that Albugo sp. do not strongly affect immune responses and leave distinct branches of the immune signaling network intact. To validate our findings and to get mechanistic insights, we tested a panel of A. thaliana mutant plants with induced or compromised immunity for susceptibility to different biotrophic pathogens. Our findings suggest that the biotroph pathogen Albugo selectively interferes with host defense under different environmental and competitive pressures to maintain its ecological niche dominance. Adaptation to host immune responses while maintaining a partially active host immunity seems advantageous against competitors. We suggest a model for future research that considers not only host-microbe but in addition microbe-microbe and microbe-host environment factors.

Integrated analysis of proteome and transcriptome changes in the mucopolysaccharidosis type VII mouse hippocampus

Mucopolysaccharidosis type VII (MPS VII) is a lysosomal storage disease caused by the deficiency of β-glucuronidase. In this study, we compared the changes relative to normal littermates in the proteome and transcriptome of the hippocampus in the C57Bl/6 mouse model of MPS VII, which has well-documented histopathological and neurodegenerative changes. A completely different set of significant changes between normal and MPS VII littermates were found in each assay. Nevertheless, the functional annotation terms generated by the two methods showed agreement in many of the processes, which also corresponded to known pathology associated with the disease. Additionally, assay-specific changes were found, which in the proteomic analysis included mitochondria, energy generation, and cytoskeletal differences in the mutant, while the transcriptome differences included immune, vesicular, and extracellular matrix changes. In addition, the transcriptomic changes in the mutant hippocampus were concordant with those in a MPS VII mouse caused by the same mutation but on a different background inbred strain.

Skin Barrier Defects Caused by Keratinocyte-Specific Deletion of ADAM17 or EGFR Are Based on Highly Similar Proteome and Degradome Alterations

Keratinocyte-specific deletion of ADAM17 in mice impairs terminal differentiation of keratinocytes leading to severe epidermal barrier defects. Mice deficient for ADAM17 in keratinocytes phenocopy mice with a keratinocyte-specific deletion of epidermal growth factor receptor (EGFR), which highlights the role of ADAM17 as a "ligand sheddase" of EGFR ligands. In this study, we aim for the first proteomic/degradomic approach to characterize the disruption of the ADAM17-EGFR signaling axis and its consequences for epidermal barrier formation. Proteomic profiling of the epidermal proteome of mice deficient for either ADAM17 or EGFR in keratinocytes at postnatal days 3 and 10 revealed highly similar protein alterations for ADAM17 and EGFR deficiency. These include massive proteome alterations of structural and regulatory components important for barrier formation such as transglutaminases, involucrin, filaggrin, and filaggrin-2. Cleavage site analysis using terminal amine isotopic labeling of substrates revealed increased proteolytic processing of S100 fused-type proteins including filaggrin-2. Alterations in proteolytic processing are supported by altered abundance of numerous proteases upon keratinocyte-specific Adam17 or Egfr deletion, among them kallikreins, cathepsins, and their inhibitors. This study highlights the essential role of proteolytic processing for maintenance of a functional epidermal barrier. Furthermore, it suggests that most defects in formation of the postnatal epidermal barrier upon keratinocyte-specific ADAM17 deletion are mediated via EGFR.

Thousand and one ways to quantify and compare protein abundances in label-free bottom-up proteomics

How to process and analyze MS data to quantify and statistically compare protein abundances in bottom-up proteomics has been an open debate for nearly fifteen years. Two main approaches are generally used: the first is based on spectral data generated during the process of identification (e.g. peptide counting, spectral counting), while the second makes use of extracted ion currents to quantify chromatographic peaks and infer protein abundances based on peptide quantification. These two approaches actually refer to multiple methods which have been developed during the last decade, but were submitted to deep evaluations only recently. In this paper, we compiled these different methods as exhaustively as possible. We also summarized the way they address the different problems raised by bottom-up protein quantification such as normalization, the presence of shared peptides, unequal peptide measurability and missing data. This article is part of a Special Issue entitled: Plant Proteomics--a bridge between fundamental processes and crop production, edited by Dr. Hans-Peter Mock.

Methods and applications of absolute protein quantification in microbial systems

In the last years the scientific community faced an increased need to provide high-quality data on the concentration of single proteins within a cell. Especially against the background of the fast evolving field of systems biology this does not only apply for a few proteins but preferably for the whole proteome of the organism. Therefore there has been a rapid development from pure identification of proteins via characterization of changes between different conditions by relative protein quantification towards determination of absolute protein amounts for hundreds of protein species in a cell. This review aims for discussion of different small-scale and large-scale approaches for absolute protein quantification in bacterial cells to picture biological processes and explore life in deeper detail. The presented advantages and limitations of various methods may provide interested researchers help to appraise available methods, select the most appropriate technique and avoid common pitfalls during determination of protein concentration in a complex sample.

Metabolic Engineering toward Sustainable Production of Nylon-6

Nylon-6 is a bulk polymer used for many applications. It consists of the non-natural building block 6-aminocaproic acid, the linear form of caprolactam. Via a retro-synthetic approach, two synthetic pathways were identified for the fermentative production of 6-aminocaproic acid. Both pathways require yet unreported novel biocatalytic steps. We demonstrated proof of these bioconversions by in vitro enzyme assays with a set of selected candidate proteins expressed in Escherichia coli. One of the biosynthetic pathways starts with 2-oxoglutarate and contains bioconversions of the ketoacid elongation pathway known from methanogenic archaea. This pathway was selected for implementation in E. coli and yielded 6-aminocaproic acid at levels up to 160 mg/L in lab-scale batch fermentations. The total amount of 6-aminocaproic acid and related intermediates generated by this pathway exceeded 2 g/L in lab-scale fed-batch fermentations, indicating its potential for further optimization toward large-scale sustainable production of nylon-6.

Computational Methods in Mass Spectrometry-Based Proteomics

This chapter introduces computational methods used in mass spectrometry-based proteomics, including those for addressing the critical problems such as peptide identification and protein inference, peptide and protein quantification, characterization of posttranslational modifications (PTMs), and data-independent acquisitions (DIA). The chapter concludes with emerging applications of proteomic techniques, such as metaproteomics, glycoproteomics, and proteogenomics.

Quantitation of Vacuolar Sugar Transporter Abundance Changes Using QconCAT Synthtetic Peptides

Measurements of protein abundance changes are important for biological conclusions on protein-related processes such as activity or complex formation. Proteomic analyses in general are almost routine tasks in many laboratories, but a precise and quantitative description of (absolute) protein abundance changes require careful experimental design and precise data quality. Today, a vast choice of metabolic labeling and label-free quantitation protocols are available, but the trade-off between quantitative precision and proteome coverage of quantified proteins including missing value problems remain. Here, we provide an example of a targeted proteomic approach using artificial standard proteins consisting of concatenated peptides of interest (QconCAT) to specifically quantify abiotic stress-induced abundance changes in low abundant vacuolar transporters. An advantage of this approach is the reliable quantitation of alimited set of low-abundant target proteins throughout different conditions. We show that vacuolar ATPase AVP1 and sugar transporters of the ERDL (early responsive to dehydration-like) family and TMT2 (tonoplast monosaccharide transporter 2) showed increased abundance upon salt stress.

Mass Spectrometry-Based Protein Quantification

Quantification of individual proteins and even entire proteomes is an important theme in proteomics research. Quantitative proteomics is an approach to obtain quantitative information about proteins in a sample. Compared to qualitative or semi-quantitative proteomics, this approach can provide more insight into the effects of a specific stimulus, such as a change in the expression level of a protein and its posttranslational modifications, or to a panel of proposed biomarkers in a given disease state. Proteomics methodologies, along with a variety of bioinformatics approaches, are a major tool in quantitative proteomics. As the theory and technological aspects underlying the proteomics methodologies will be extensively described in Chap. 20 , and protein identification as a prerequisite of quantification has been discussed in Chap. 17 , we will focus on the quantitative proteomics bioinformatics algorithms and software tools in this chapter. Our goal is to provide researchers and newcomers a rational framework to select suitable bioinformatics tools for data analysis, interpretation, and integration in protein quantification. Before doing so, a brief overview of quantitative proteomics is provided.

Accuracy and Reproducibility in Quantification of Plasma Protein Concentrations by Mass Spectrometry without the Use of Isotopic Standards

Background

Quantitative proteomic analysis with mass spectrometry holds great promise for simultaneously quantifying proteins in various biosamples, such as human plasma. Thus far, studies addressing the reproducible measurement of endogenous protein concentrations in human plasma have focussed on targeted analyses employing isotopically labelled standards. Non-targeted proteomics, on the other hand, has been less employed to this end, even though it has been instrumental in discovery proteomics, generating large datasets in multiple fields of research.

Results

Using a non-targeted mass spectrometric assay (LCMS^E), we quantified abundant plasma proteins (43 mg/mL—40 ug/mL range) in human blood plasma specimens from 30 healthy volunteers and one blood serum sample (ProteomeXchange: PXD000347). Quantitative results were obtained by label-free mass spectrometry using a single internal standard to estimate protein concentrations. This approach resulted in quantitative results for 59 proteins (cut off ≥11 samples quantified) of which 41 proteins were quantified in all 31 samples and 23 of these with an inter-assay variability of ≤ 20%. Results for 7 apolipoproteins were compared with those obtained using isotope-labelled standards, while 12 proteins were compared to routine immunoassays. Comparison of quantitative data obtained by LCMS^E and immunoassays showed good to excellent correlations in relative protein abundance (r = 0.72–0.96) and comparable median concentrations for 8 out of 12 proteins tested. Plasma concentrations of 56 proteins determined by LCMS^E were of similar accuracy as those reported by targeted studies and 7 apolipoproteins quantified by isotope-labelled standards, when compared to reference concentrations from literature.

Conclusions

This study shows that LCMS^E offers good quantification of relative abundance as well as reasonable estimations of concentrations of abundant plasma proteins.

Proteomic Analysis of Dhh1 Complexes Reveals a Role for Hsp40 Chaperone Ydj1 in Yeast P-Body Assembly

P-bodies (PB) are ribonucleoprotein (RNP) complexes that aggregate into cytoplasmic foci when cells are exposed to stress. Although the conserved mRNA decay and translational repression machineries are known components of PB, how and why cells assemble RNP complexes into large foci remain unclear. Using mass spectrometry to analyze proteins immunoisolated with the core PB protein Dhh1, we show that a considerable number of proteins contain low-complexity sequences, similar to proteins highly represented in mammalian RNP granules. We also show that the Hsp40 chaperone Ydj1, which contains an low-complexity domain and controls prion protein aggregation, is required for the formation of Dhh1-GFP foci on glucose depletion. New classes of proteins that reproducibly coenrich with Dhh1-GFP during PB induction include proteins involved in nucleotide or amino acid metabolism, glycolysis, transfer RNA aminoacylation, and protein folding. Many of these proteins have been shown to form foci in response to other stresses. Finally, analysis of RNA associated with Dhh1-GFP shows enrichment of mRNA encoding the PB protein Pat1 and catalytic RNAs along with their associated mitochondrial RNA-binding proteins. Thus, global characterization of PB composition has uncovered proteins important for PB assembly and evidence suggesting an active role for RNA in PB function.

Proteomic analysis of extracellular vesicles derived from Mycobacterium tuberculosis

The release of extracellular vesicles, also known as outer membrane vesicles, membrane vesicles, exosomes, and microvesicles, is an evolutionarily conserved phenomenon from bacteria to eukaryotes. It has been reported that Mycobacterium tuberculosis releases extracellular vesicles harboring immunologically active molecules, and these extracellular vesicles have been suggested to be applicable in vaccine development and biomarker discovery. However, the comprehensive proteomic analysis has not been performed for M. tuberculosis extracellular vesicles. In this study, we identified a total of 287 vesicular proteins by four LC-MS/MS analyses with high confidence. In addition, we identified several vesicular proteins associated with the virulence of M. tuberculosis. This comprehensive proteome profile will help elucidate the pathogenic mechanism of M. tuberculosis. The data have been deposited to the ProteomeXchange with identifier PXD001160 (http://proteomecentral.proteomexchange.org/dataset/PXD001160).

Quantitative Differences in the Urinary Proteome of Siblings Discordant for Type 1 Diabetes Include Lysosomal Enzymes

Individuals with type 1 diabetes (T1D) often have higher than normal blood glucose levels, causing advanced glycation end product formation and inflammation and increasing the risk of vascular complications years or decades later. To examine the urinary proteome in juveniles with T1D for signatures indicative of inflammatory consequences of hyperglycemia, we profiled the proteome of 40 T1D patients with an average of 6.3 years after disease onset and normal or elevated HbA1C levels, in comparison with a cohort of 41 healthy siblings. Using shotgun proteomics, 1036 proteins were identified, on average, per experiment, and 50 proteins showed significant abundance differences using a Wilcoxon signed-rank test (FDR q-value ≤ 0.05). Thirteen lysosomal proteins were increased in abundance in the T1D versus control cohort. Fifteen proteins with functional roles in vascular permeability and adhesion were quantitatively changed, including CD166 antigen and angiotensin-converting enzyme 2. α-N-Acetyl-galactosaminidase and α-fucosidase 2, two differentially abundant lysosomal enzymes, were detected in western blots with often elevated quantities in the T1D versus control cohort. Increased release of proteins derived from lysosomes and vascular epithelium into urine may result from hyperglycemia-associated inflammation in the kidney vasculature.

Quantitative proteomic analysis of formalin-fixed, paraffin-embedded clear cell renal cell carcinoma tissue using stable isotopic dimethylation of primary amines

Background

Formalin-fixed, paraffin-embedded (FFPE) tissues represent the most abundant resource of archived human specimens in pathology. Such tissue specimens are emerging as a highly valuable resource for translational proteomic studies. In quantitative proteomic analysis, reductive di-methylation of primary amines using stable isotopic formaldehyde variants is increasingly used due to its robustness and cost-effectiveness.

Results

In the present study we show for the first time that isotopic amine dimethylation can be used in a straightforward manner for the quantitative proteomic analysis of FFPE specimens without interference from formalin employed in the FFPE process. Isotopic amine dimethylation of FFPE specimens showed equal labeling efficiency as for cryopreserved specimens. For both FFPE and cryopreserved specimens, differential labeling of identical samples yielded highly similar ratio distributions within the expected range for dimethyl labeling. In an initial application, we profiled proteome changes in clear cell renal cell carcinoma (ccRCC) FFPE tissue specimens compared to adjacent non–malignant renal tissue. Our findings highlight increased levels of glyocolytic enzymes, annexins as well as ribosomal and proteasomal proteins.

Conclusion

Our study establishes isotopic amine dimethylation as a versatile tool for quantitative proteomic analysis of FFPE specimens and underlines proteome alterations in ccRCC.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1768-x) contains supplementary material, which is available to authorized users.

A proteomic profiling of laser-microdissected lung adenocarcinoma cells of early lepidic-types

Background

In the new pathologic classification of lung adenocarcinoma proposed by IASLC/ATS/ERS in 2011, lepidic type adenocarcinomas are constituted by three subtypes; adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA) and lepidic predominant invasive adenocarcinoma (LPIA). Although these subtypes are speculated to show sequential progression from preinvasive lesion to invasive lung cancer, changes of protein expressions during these processes have not been fully studied yet. This study aims to glimpse a proteomic view of the early lepidic type lung adenocarcinomas.

Methods

A total of nine formalin-fixed and paraffin-embedded (FFPE) lepidic type lung adenocarcinoma tissues were selected from our archives, three tissues each in AIS, MIA and LPIA. The tumor and peripheral non-tumor cells in these FFPE tissues were collected with laser microdissection (LMD). Using liquid chromatography-tandem mass spectrometry (MS/MS), protein compositions were compared with respect to the peptide separation profiles among tumors collected from three types of tissues, AIS, MIA and LPIA. Proteins identified were semi-quantified by spectral counting-based or identification-based approach, and statistical evaluation was performed by pairwise G-tests.

Results

A total of 840 proteins were identified. Spectral counting-based semi-quantitative comparisons of all identified proteins through AIS to LPIA have revealed that the protein expression profile of LPIA was significantly differentiated from other subtypes. 70 proteins including HPX, CTTN, CDH1, EGFR, MUC1 were found as LPIA-type marker candidates, 15 protein candidates for MIA-type marker included CRABP2, LMO7, and RNPEP, and 26 protein candidates for AIS-type marker included LTA4H and SOD2. The STRING gene set enrichment resulted from the protein-protein interaction (PPI) network analysis suggested that AIS was rather associated with pathways of focal adhesion, adherens junction, tight junction, that MIA had a strong association predominantly with pathways of proteoglycans in cancer and with PI3K-Akt. In contrast, LPIA was associated broadly with numerous tumor-progression pathways including ErbB, Ras, Rap1 and HIF-1 signalings.

Conclusions

The proteomic profiles obtained in this study demonstrated the technical feasibility to elucidate protein candidates differentially expressed in FFPE tissues of LPIA. Our results may provide candidates of disease-oriented proteins which may be related to mechanisms of the early-stage progression of lung adenocarcinoma.

Electronic supplementary material

The online version of this article (doi:10.1186/s40169-015-0064-3) contains supplementary material, which is available to authorized users.

Characterisation of the Manduca sexta sperm proteome: Genetic novelty underlying sperm composition in Lepidoptera

The application of mass spectrometry based proteomics to sperm biology has greatly accelerated progress in understanding the molecular composition and function of spermatozoa. To date, these approaches have been largely restricted to model organisms, all of which produce a single sperm morph capable of oocyte fertilisation. Here we apply high-throughput mass spectrometry proteomic analysis to characterise sperm composition in Manduca sexta, the tobacco hornworm moth, which produce heteromorphic sperm, including one fertilisation competent (eupyrene) and one incompetent (apyrene) sperm type. This resulted in the high confidence identification of 896 proteins from a co-mixed sample of both sperm types, of which 167 are encoded by genes with strict one-to-one orthology in Drosophila melanogaster. Importantly, over half (55.1%) of these orthologous proteins have previously been identified in the D. melanogaster sperm proteome and exhibit significant conservation in quantitative protein abundance in sperm between the two species. Despite the complex nature of gene expression across spermatogenic stages, a significant correlation was also observed between sperm protein abundance and testis gene expression. Lepidopteran-specific sperm proteins (e.g., proteins with no homology to proteins in non-Lepidopteran taxa) were present in significantly greater abundance on average than those with homology outside the Lepidoptera. Given the disproportionate production of apyrene sperm (96% of all mature sperm in Manduca) relative to eupyrene sperm, these evolutionarily novel and highly abundant proteins are candidates for possessing apyrene-specific functions. Lastly, comparative genomic analyses of testis-expressed, ovary-expressed and sperm genes identified a concentration of novel sperm proteins shared amongst Lepidoptera of potential relevance to the evolutionary origin of heteromorphic spermatogenesis. As the first published Lepidopteran sperm proteome, this whole-cell proteomic characterisation will facilitate future evolutionary genetic and developmental studies of heteromorphic sperm production and parasperm function. Furthermore, the analyses presented here provide useful annotation information regarding sex-biased gene expression, novel Lepidopteran genes and gene function in the male gamete to complement the newly sequenced and annotated Manduca genome.

Label-free LC-MS/MS quantitative analysis of aqueous humor from keratoconic and normal eyes

PURPOSE

The etiology of keratoconus (KC) and the factors governing its progression are not well understood. It has been suggested that this disease might be caused by biochemical alterations in the cornea; changes in the expression profiles of human aqueous humor (hAH) proteins have been observed in some diseases. To gain a new insight into the molecular mechanisms of KC pathology, we examined the hAH proteomes of those in the advanced stages of this disease. We used a high-throughput mass spectrometry approach to compare hAH protein expression in patients with KC and in control subjects.

METHODS

Aqueous humor samples were acquired from five keratoconus patients during keratoplasty surgery and from five myopic control subjects during phakic intraocular lens implantation. Quantitative mass spectrometry analysis using spectral counting was performed to determine the relative amounts of hAH proteins in the samples from KC patients and control individuals.

RESULTS

All KC patients included in the study presented severe keratoconus (K2 >52 D), and slit-lamp examination revealed microfolds in Descemet's membrane, without clinical signs of hydrops. We found significant differences between the expression levels of 16 proteins in the two groups. In KC samples, seven proteins were overexpressed and nine were underexpressed in comparison with the control group. Gene ontology analysis revealed that these deregulated proteins are implicated in several biologic processes, such as the regulation of proteolysis, responses to hypoxia, and responses to hydrogen peroxide, among others.

CONCLUSIONS

The protein expression profiles in hAH from KC patients and myopic control subjects differ significantly. This result suggests that some components of the hAH proteome are involved in this disease. Further in-depth analysis of the hAH proteome should provide a better understanding of the mechanisms governing the pathophysiology of KC.

Proteomic analysis of the palmitate-induced myotube secretome reveals involvement of the annexin A1-formyl peptide receptor 2 (FPR2) pathway in insulin resistance

Elevated levels of the free fatty acid palmitate are found in the plasma of obese patients and induce insulin resistance. Skeletal muscle secretes myokines as extracellular signaling mediators in response to pathophysiological conditions. Here, we identified and characterized the skeletal muscle secretome in response to palmitate-induced insulin resistance. Using a quantitative proteomic approach, we identified 36 secretory proteins modulated by palmitate-induced insulin resistance. Bioinformatics analysis revealed that palmitate-induced insulin resistance induced cellular stress and modulated secretory events. We found that the decrease in the level of annexin A1, a secretory protein, depended on palmitate, and that annexin A1 and its receptor, formyl peptide receptor 2 agonist, played a protective role in the palmitate-induced insulin resistance of L6 myotubes through PKC-θ modulation. In mice fed with a high-fat diet, treatment with the formyl peptide receptor 2 agonist improved systemic insulin sensitivity. Thus, we identified myokine candidates modulated by palmitate-induced insulin resistance and found that the annexin A1- formyl peptide receptor 2 pathway mediated the insulin resistance of skeletal muscle, as well as systemic insulin sensitivity.